Artificial Intelligence and Sensors in Smart Buildings
A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Intelligent Sensors".
Deadline for manuscript submissions: closed (10 April 2024) | Viewed by 728
Special Issue Editor
Special Issue Information
Dear Colleagues,
The distribution of the population has dramatically changed over recent decades. Since 1980, the shift from rural to urban migration challenged peoples’ way of cohabiting. Nowadays, 60% of the global population lives in cities. This assortment has led to inefficient connectivity, ineffective transportation, pollution, weak security, and energy waste. Therefore, guaranteeing sustainable growth of cities demands scalable technological innovations, which must provide quality of life by maximizing resources. Humanity is currently living in the Big Data age.
One of the key pillars of Big Data is the notion that more data may lead to greater knowledge (Big Data’s mythological definition) of problems and, ultimately, a more accurate solution to those. Data in the building field are plentiful and produced fast. Various sources contribute data during the course of a building’s life cycle (design, construction, and maintenance). Stakeholders including customers, local suppliers, operational and technical teams, CEOs, and occupants, for example, continually contribute data, suggesting that the buildings sector creates a Big Data environment. The expert operators use automation systems to handle building objects in an attempt to give comfort to occupants efficiently.
In the Big Data era, Artificial Intelligence (A.I.) techniques and Internet of Things (IoT) systems have increased the capabilities of building systems by allowing them to learn, reason, and adapt to new scenarios. Consequently, transitioning from human to data-driven systems has formed a field known as Smart Buildings. Smart Buildings deal with optimizing buildings’ performance by leveraging Information and Communication Technology (ICT).
This field derives into two main currents from a computer science view, which focuses first on the occupant’s well-being (e.g., indoor air quality) and second on the operativity of the underlying architecture of the Building Management System (BMS) (e.g., Big Data storage). The occupants’ well-being sub-fields study how users can deal with buildings’ diverse energy sources (e.g., solar panels and wind turbines), reduce energy consumption, and enhance services, such as thermal comfort, healthcare, indoor navigation, air quality, illumination, and localization. On the other hand, BMS’s architecture studies focus on optimizing the underlying system that supports the services for occupants.
Therefore, it is common to find research on integrating heterogeneous data and devices, enhancing the BMS interoperability and adaptability, and hierarchical decision-making algorithms in BMS. Occupants’ well-being and BMS’s architecture studies are intrinsically tied.
This Special Issue is dedicated to research aimed at pushing back the boundaries of intelligent building development.
Since BMS gathers voluminous data quickly, obtaining value from heterogeneous and geographically dispersed datasets generated from IoT is a major challenge. The lack of integration and context causes data silos, inflexibility of BMS, and decision-making conflicts. Underestimating these issues is risky for the scalability of BMS, thence risky for the sustainable development of cities.
Prof. Dr. Christophe Nicolle
Guest Editor
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Keywords
- smart buildings
- artificial intelligence
- Internet of Things
- building management system
- sustainable cities
